Assessing the Quality of Heart Rate Variability Estimated from Wrist and Finger PPG: A Novel Approach Based on Cross-Mapping Method

• Published in: Sensors (Basel, Switzerland) Vol. 20; no. 11; p. 3156
• Main Authors: Nardelli, Mimma, Vanello, Nicola, Galperti, Guenda, Greco, Alberto, Scilingo, Enzo Pasquale
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI 02.06.2020; MDPI AG
• Subjects: Adult; cross-mapping; Electrocardiography; Female; Fingers; Heart Rate; heart rate variability (HRV); Humans; kurtosis; Male; photoplethysmographic (PPG) signal; Photoplethysmography; pulse rate variability (PRV); Reproducibility of Results; Shannon entropy; Signal Processing, Computer-Assisted; Wrist; photoplethysmographic (PPG) signal; pulse rate variability (PRV); phase space reconstruction; signal quality indexes; heart rate variability (HRV); Shannon entropy; cross-mapping; kurtosis; wearable monitoring systems
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s20113156

The non-invasiveness of photoplethysmographic (PPG) acquisition systems, together with their cost-effectiveness and easiness of connection with IoT technologies, is opening up to the possibility of their widespread use. For this reason, the study of the reliability of PPG and pulse rate variability (PRV) signal quality has become of great scientific, technological, and commercial interest. In this field, sensor location has been demonstrated to play a crucial role. The goal of this study was to investigate PPG and PRV signal quality acquired from two body locations: finger and wrist. We simultaneously acquired the PPG and electrocardiographic (ECG) signals from sixteen healthy subjects (aged 28.5 ± 3.5, seven females) who followed an experimental protocol of affective stimulation through visual stimuli. Statistical tests demonstrated that PPG signals acquired from the wrist and the finger presented different signal quality indexes (kurtosis and Shannon entropy), with higher values for the wrist-PPG. Then we propose to apply the cross-mapping (CM) approach as a new method to quantify the PRV signal quality. We found that the performance achieved using the two sites was significantly different in all the experimental sessions (p < 0.01), and the PRV dynamics acquired from the finger were the most similar to heart rate variability (HRV) dynamics.